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Related Experiment Videos

Comparing breast cancer case identification using HMO computerized diagnostic data and SEER data.

Sharon J Rolnick1, Gene Hart, Mary B Barton

  • 1HealthPartners Research Foundation, PO Box 1524, MS 21111R, Minneapolis, MN 55440-1524, USA. cheri.j.rolnick@healthpartners.com

The American Journal of Managed Care
|May 6, 2004
PubMed
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Health maintenance organization (HMO) computerized databases show high sensitivity for identifying new breast cancer cases. However, positive predictive value (PPV) was initially low due to difficulties distinguishing prevalent from incident cases.

Area of Science:

  • Oncology
  • Health Informatics
  • Epidemiology

Background:

  • Accurate identification of incident cancer cases is crucial for epidemiological research and public health surveillance.
  • Health Maintenance Organizations (HMOs) possess extensive patient data that could potentially be leveraged for cancer case ascertainment.
  • Traditional cancer registries, such as Surveillance, Epidemiology, and End Results (SEER) programs, are valuable but may not capture all cases within integrated healthcare systems.

Purpose of the Study:

  • To evaluate the sensitivity and positive predictive value (PPV) of computerized diagnostic data within HMOs for identifying incident breast cancer cases.
  • To compare the performance of HMO computerized data against established cancer registries (SEER) as a criterion standard.

Main Methods:

  • An algorithm using computerized diagnostic codes was developed to identify incident breast cancer cases in an HMO without a cancer registry.

Related Experiment Videos

  • This case-identification approach was replicated in two additional HMOs with existing SEER registries.
  • Sensitivity and PPV were calculated using SEER registries as the gold standard for validation.

    • Main Results:

    • HMO databases demonstrated high overall sensitivity for detecting incident breast cancer, ranging from 0.92 to 0.99.
    • Positive predictive value (PPV) was initially low (0.34-0.44) but significantly improved over time, reaching 0.83-0.92 in the final year as prevalent cases were excluded.
    • A review indicated that while SEER data usually identified cases, some cases identified by HMOs were not linked to the health plan in SEER.

    Conclusions:

    • Computerized databases in HMOs are highly sensitive for identifying incident breast cancer cases.
    • The PPV of these databases is limited in the first year due to the inability to differentiate prevalent from incident cases.
    • Sole reliance on SEER data may lead to undercounting of breast cancer cases within HMO populations.